首页> 外文会议>International conference on industrial engineering and other applications of applied intelligent systems;IEA/AIE 2011 >Robot with Two Ears Listens to More than Two Simultaneous Utterances by Exploiting Harmonic Structures
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Robot with Two Ears Listens to More than Two Simultaneous Utterances by Exploiting Harmonic Structures

机译:两只耳朵的机器人通过利用谐波结构聆听两个以上的同时发声

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In real-world situations, people often hear more than two simultaneous sounds. For robots, when the number of sound sources exceeds that of sensors, the situation is called under'-determined, and robots with two ears need to deal with this situation. Some studies on under-determined sound source separation use Ll-norm minimization methods, but the performance of automatic speech recognition with separated speech signals is poor due to its spectral distortion. In this paper, a two-stage separation method to improve separation quality with low computational cost is presented. The first stage uses a Ll-norm minimization method in order to extract the harmonic structures. The second stage exploits reliable harmonic structures to maintain acoustic features. Experiments that simulate three utterances recorded by two microphones in an anechoic chamber show that our method improves speech recognition correctness by about three points and is fast enough for real-time separation.
机译:在现实世界中,人们经常听到两个以上的声音。对于机器人,当声源的数量超过传感器的数量时,这种情况称为“确定”,并且需要两只耳朵的机器人来处理这种情况。关于欠定音源分离的一些研究使用L1-norm最小化方法,但是由于分离的语音信号的频谱失真,自动语音识别的性能很差。本文提出了一种两步分离方法,以较低的计算成本提高分离质量。第一阶段使用L1-范数最小化方法以提取谐波结构。第二阶段利用可靠的谐波结构来维持声学特征。模拟在消声室内由两个麦克风记录的三种发音的实验表明,我们的方法将语音识别正确性提高了大约三点,并且足够快地进行实时分离。

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